Katarxis Nº 3

Design methods, emergence,

and collective intelligence

Nikos A. Salingaros

Department of Applied Mathematics

University of Texas at San Antonio

San
Antonio, Texas 78249.

salingar@sphere.math.utsa.edu

Abstract:
The two methods of adaptive top-down and bottom-up design
are shown to be theoretically equivalent. Even though they
differ drastically in their application, each one can help
the other, and they may even be combined in a particular
project. Both cases rely on traditional solutions encoded
into the built environment, which represents the product of
our collective intelligence. Implementing this realization
to rebuild our world can lead to an unprecedented degree of
support for human life from architectural and urban
structures.

1.Introduction

2.Darwinian design

3.Sorting algorithms as
an analogy for design

4.Darwinian evolution of
algorithms

5.Understanding patterns
and buildings

6.Top-down versus
bottom-up design

7.Collective intelligence

8.Emergence and
self-organization

9.Adaptivity and feedback

10.Conclusion

1. Introduction.

Today, practicing architects use design procedures that have
been current for the last eighty years or so. Even though
those procedures are taught by architecture schools the
world over, many critics have argued that together they do
not comprise a design method that produces pleasant,
comfortable, and useful buildings. For example, the
architect and urbanist Léon Krier asserts that they
represent personal caprices rather than solid foundations
for design, as evident by the uniformly unpleasant quality
of the results [1]. Instead of providing a useful design
basis, architectural theorists are alleged to be clinging
stubbornly to narrow and outdated ideas of the 1920s,
exerting thought and energy to create a corpus of work that
is irrelevant to human needs.

Critics of contemporary architecture argue that a serious
problem for mankind developed when design began to be driven
by ideology, so that appearance, form, evaluation, and
justification were no longer related to a building's use by
human beings. In this intellectual atmosphere, it is very
easy to ignore the effect that built form has on human
sensibilities, and to use abstract criteria to justify a
particular building style. Those criteria can then be
dictated by ideas that have nothing to do with either human
beings, or their relationship to the built environment, and
which frequently turn out to destroy this critical
relationship [1].

I will argue that we face a totally confused situation, and
that the only way out is to understand adaptive design
methods based on scientific analysis. I am well aware that
this goal was already pursued in the 1960s, without many
lasting consequences. Architecture and design should be
based on artistic sensibilities. Nevertheless, I suggest
that so many egregious errors are now part of the basic
credo of today's architects that we can no longer continue
to work in this intuitive fashion. The artistic/intuitive
method is certainly valid within a culture of traditional
buildings, but it fails totally when destructive influences
act on design. There are indications that this is
overwhelmingly the case today.

2. Darwinian design.

An earlier paper [2] proposed that all good design is
necessarily adaptive, and that the optimal method of
achieving an adaptive design follows a Darwinian process. By
this I mean an evolution of a group of similar competing
design solutions for a particular project, of which the most
adaptive is selected in stages. This process requires a set
of selection criteria that are used as the basis of
selection or "culling" from amongst the various alternative
design choices that are generated. I am describing an
intentional procedure, not to be confused with an entirely
random proliferation devoid of selection.

As in biological evolution, the selection criteria strongly
influence what the final result looks like. Therefore, a set
of selection criteria based on adaptivity will generate an
adaptive design; whereas a set of criteria based on
comparison to certain prototypes will guarantee that the end
result will resemble that reference prototype. In biology,
adaptive selection to different environments has taken place
to produce what we today regard as entirely different
animals -- starting from the same common ancestor.

Selection via comparison to a prototype is not necessarily
bad, if the prototype itself is adapted to the uses of the
required design solution. This can happen only if the
prototype has been produced by evolutionary adaptation.
While the end result of copying a prototype may not be the
most original possible, it does guarantee a strong measure
of usefulness, as the derived design inherits the adaptive
properties of the original. This is the method of
traditional design: copy a set of prototypes, which
themselves have evolved by selection over millennia to adapt
to particular uses, and the end result is guaranteed to be
adequate. The only problem arises if local forces are not
accommodated by the prototype.

Copying a prototype leads to disaster when that prototype
has not evolved, but is imposed (i.e. is defined ad hoc).
This occurred on a massive scale during the twentieth
century, when arbitrary geometrical forms were presented as
architectural and urban prototypes. Those prototypes were
based on abstract reasoning that itself had only a tenuous
connection to social and philosophical concepts; none of
which relates to human activities, functions, or
sensibilities. Matching to those prototypes produces
non-adaptive designs that never achieve any degree of user
comfort, either physically or psychologically [1, 2].

Nevertheless, twentieth-century design based on matching to
simple abstract prototypes was extraordinarily successful,
because it was very easy to use in practice [2]. This is
demonstrated by counting the number of steps in the design
method. We can estimate very roughly the number of steps in
an intentional Darwinian processes corresponding to
selections in each of the above-mentioned methods. In
order-of-magnitude estimates: (1) modernist design requires
only a few (usually less than five) steps to match pure
geometric prototypes; (2) traditional vernacular design,
including Classical, typically requires on the order of
twenty to thirty steps to match traditionally-derived
prototypes; (3) an innovative adaptive design that is not
anchored to any traditional form may in general require up
to one-hundred steps to evolve its adaptations.

Strictly in terms of economy in the number of design steps
-- which corresponds to hard mental effort at developing
design variants, and choosing the most appropriate ones
among them -- modernist design wins out over any other
design method. So, we have to recognize its tremendous
advantage of economy. This economy in turn helps to explain
modernism's widespread adoption during the twentieth century
[2]. To replace modernist design with an adaptive design
method, one has to be convinced of the benefits of such a
change.

3. Sorting algorithms as an analogy for design.

An excursion into computing will serve to illustrate two
basic approaches to design: (i) intentional, top-down
design, versus (ii) evolved, bottom-up design. It will also
help us to understand adaptivity. I claim that both
techniques can be made to work to achieve a final product
that is of comparable utility. I will then argue that they
are equivalent in an abstract mathematical way. The central
question of design adaptivity will only be addressed
afterwards.

A recent result in computer science has important
implications for design. This result is not widely known in
architectural or urbanist circles, so I present it here. It
is useful to consider design as an algorithm: a set of
instructions to be followed in order to achieve a particular
result. There are deep connections between architecture and
computer science, which first became obvious in the success
that the "patterns" introduced by Christopher Alexander
et. al. in architecture [3] eventually had in software
[4].

The present discussion is distinct from design patterns. One
of the simplest possible programs is a number-sorting
program, which takes a list of numbers and sorts them into
increasing magnitude. The reason such a program is so simple
is that its generative components -- corresponding so to
speak to the DNA in a biological entity -- are basically
two: comparing, and switching. There are instructions to
compare two numbers to see which is greater, and other
instructions to either leave these two numbers in their
original order, or to switch them. By a judicious
combination of comparing and switching instructions, one
creates a number-sorting algorithm.

In the specific example to be discussed here, a list of 16
numbers is sorted. This is known as a "sorting network for
n = 16 ". It became something of a challenge for the
smartest computer programmers to write the shortest (i.e.
optimal) program that could sort a list of numbers. The
shortest programs for this task were written using fewer and
fewer exchanges as follows: with only 65 exchanges in 1962;
63 exchanges in 1964; 62 exchanges in 1969; and 60 exchanges
in 1969 [5]. The question remains open whether it is
possible to write an even shorter program to achieve the
same task.

4. Darwinian evolution of algorithms.

The computer scientist Danny Hillis developed a Darwinian
setting for evolving number-sorting algorithms [5, 6]. By
generating an enormous variety of programs containing
randomly-distributed switching components, he selected those
that achieved some partial success in sorting number lists.
(Actually, Hillis took the first 32 exchanges from the most
successful existing programs for sorting 16 numbers, and
allowed the number and character of all subsequent exchanges
to evolve). He then combined those programs or introduced
random shufflings in each one, and after each shuffling
checked them for sorting ability. By doing this an enormous
number of times on one of the most powerful computers (which
he himself designed and built), Hillis was able to evolve a
sorting algorithm starting from a random collection of basic
components. The result was a sorting algorithm with only 61
exchanges.

The results are profound in their implication. First the
obvious result: a Darwinian process evolved a program out of
a mishmash of switching instructions, which is just as
efficient as those developed by the best human minds. The
second result was totally unexpected: Hillis cannot
understand how the evolved algorithm actually works [6,
7]. The 30 or so evolved exchanges are in a configuration
that does not reveal a recognizable sorting pattern. It is
reasonable to suppose, then, that it is unlikely the evolved
sorting algorithm could have been written by a human
programmer.

This single example demonstrates that a Darwinian process
need not necessarily result in an understandable pattern.
(This does not mean, however, that all the results of
Darwinian selection cannot be understood). We can test such
evolved algorithms to make sure they are correct and
efficient, yet their internal complexity somehow escapes us.
This was revealed in one of the simplest possible algorithms
-- a sorting program for 16 numbers. Clearly, more complex
systems are bound to have an even higher, and perhaps
incomprehensible, complexity.

Human ingenuity using proven programming methods led to a
program with 60 switches, whereas a Darwinian process led to
a program with 61 switches. The results are almost exactly
comparable in their efficiency. This suggests something
about architectural design. Intentional, top-down design
that is based on evolved prototypes can indeed be compared
with evolved, bottom-up design. Both intentional and
bottom-up approaches give optimal solutions of comparable
fitness, while the results of an evolutionary approach are
in a fundamental sense unexpected.

5. Understanding patterns and buildings.

I am analyzing how design methods arise by understanding the
generation of adaptive form. The method itself is
prescriptive -- we cannot allow for the time it would take
for form to evolve in historical time, such as a cathedral
built and modified over centuries, or a city evolving over
an even longer time frame. The evolution of a design occurs
on an artificially accelerated practical time scale, either
in the planning stage before a building is put up, or during
construction. Changes can be made during construction, and
adaptive changes could also be allowed afterwards.
Nevertheless, the form at every stage is understandable, as
it adapts to its surroundings and uses.

All of nature works via complex processes that, in their
details, remain outside our understanding. The enormous
amount of physical, chemical, and biological mechanisms that
we do understand is dwarfed by the amount that we still
don't understand. Scientists respect nature's complexity,
and we are constantly trying to deepen our understanding of
its workings. Most important, we should refrain from
arbitrarily imposing our own simplified understanding on
nature itself. When we do, the result is often disastrous.
Intervention in medicine, ecology, and the environment is
most successful when we (1) use a basis of voluminous
observations of cause and effect to guide our interventions;
(2) go in with the understanding that the actual process may
be much more complex than we think [8].

Our discussion of sorting algorithms suggests that evolved
architectural and urban solutions don't necessarily have to
be understandable -- but they are nevertheless optimal
archetypes which can be copied subsequently. When Alexander
and his co-authors described architectural and urban
patterns in "A Pattern Language" [3], they explained some of
the patterns using scientific data. Other patterns they
merely presented as valid because of their repeating
occurrence, without formal proof. Indeed, one can state as a
general principle that patterns, most of which have evolved
over millennia, may not all be understandable, because we do
not yet know all the factors that generate them.

Some contemporary buildings are not understandable, but for
an entirely different reason to what was described above.
They have not evolved adaptively to any purpose; they are
arbitrary and only mean to shock by their disconnectedness
[9]. For this reason, they resemble nothing that could
possibly be considered as adaptive. Their raison d'être
is an intentional breaking up of space and form so as to
create psychological and physiological anxiety in the
observer. There is no order here to be understood; only
disorder. Our schools and media are now teaching that such a
destructive state is the pinnacle of architectural
creativity, rather than a dangerous expression of nihilism
[9].

The early modernists were equally arbitrary in an opposite
way. They rebuilt our environment with the arrogant
assumption that they understood all there is to know; that
their simplistic geometrical conception was in fact
sufficient to create architectonic and urban structures.
Furthermore, they convinced themselves that existing
complexity encoded into the built environment was not only
superfluous, but had to be eliminated because it held back
"scientific progress" [2]. They were fooled by superficial
appearances, and had only a sketchy and entirely mistaken
idea of nineteenth century science (though they boasted that
their preconceived and untested ideas were "scientific").
Such an attitude in medicine turns out to be lethal.

6. Top-down versus bottom-up design.

I wish to clear up an old problem that has prevented the
useful collaboration between two distinct schools of thought
about design. There exists a group of architects and urban
designers who follow what can loosely be termed "Classical"
rules. These impose forms which have been thought out
entirely during the planning stage. Practitioners include
formal Classical architects, Neoclassicists, and New
Urbanists, who tend to apply typologies derived from
Greco-Roman and Nineteenth Century models. Their results are
comfortable, ordered, human-scaled, and figure prominently
in the large-scale architectural and urban regeneration of
our cities [1].

The other school of design (characterized as "Structural" by
Brian Hanson and Samir Younés [10]) abandons already
developed geometrical typologies and instead evolves
solutions afresh in each instance. Practitioners here try to
evolve the design in real time, often with the explicit and
ongoing collaboration of potential users. The design -- and
building -- process is bottom-up rather than top-down. Since
a main point of the method is the continuing influence of
users to change form as it is being built, the design can
evolve into an unexpected final state, much like our result
from computer evolution mentioned above. A key tool of this
design school is the use of Alexander et. al.'s "A
Pattern Language" [3]. Those patterns are evolved solutions
for accommodating human uses and needs: they are connective
and configurational prescriptions rather than geometrical
constraints [11].

At first glance, there would appear to be little in common
between these two design approaches, yet both rely on a
Darwinian process of selection. The difference is as
follows. In the top-down design process, an intentional
Darwinian selection occurs in two parts: (i) in the past,
when the geometrical prototypes comprising the form language
were evolved to adapt to human use and sensibilities; (ii)
in virtual space in the mind of the designer before any
construction takes place. The top-down instance uses a
proven repository of forms. It is more efficient to
concentrate the secondary selection within one mind, so the
design tends to be less collaborative and more the result of
the decisions of a single person.

In the bottom-up design process, we have a very similar
division into two parts: (i) a Darwinian process has in the
past generated Alexandrine patterns; (ii) Darwinian
selection takes place further in real time during
preliminary trials and actual building. The bottom-up
instance, where a number of persons have significant input
into the form as it is evolving, has opposite
characteristics from the top-down process. Because of their
fundamentally different approaches, top-down design relies
more on geometry and an inherited form language, whereas the
bottom-up approach dispenses with geometrical prototypes and
instead works within the design constraints represented by
"patterns".

The top-down design that I am proposing consists exclusively
of traditional and classical prototypes, which have
themselves evolved over time through Darwinian selection. A
danger with top-down design is that it could employ
prototypes that have never evolved, and are thus not
adaptive to human needs. Also, it is possible to put
together perfectly adapted prototypes in a non-adaptive
manner, unless one is very sensitive to the local forces.
This problem is best handled by employing some of the
techniques from bottom-up design, which allows
self-organization as discussed later in this paper.

Bottom-up design has a much better chance for adaptation,
but the opposite potential weakness: unless it is
intentional, and selection is governed by adaptation to
human needs, it becomes random. Disorganized growth,
however, is parasitic to healthy architectural form and
urban fabric, as it is to biological tissue. Such growth is
neither adaptive, nor the result of self-organization. It
represents the proliferation of structure that does not
relate to the whole. Evolved form generates organized
complexity, whereas random growth generates disorganized
complexity [9]. Organizational principles are in general so
complex that they are best helped by evolved solutions,
which brings us back to a reliance on top-down methods of
organization (though emphatically not the imposition of
forms).

For many decades, people have assumed that top-down and
bottom-up design methods represent opposite and mutually
contradictory approaches. One can trace the famous (and very
regrettable) argument between Lewis Mumford and Jane Jacobs
to precisely this difference. I, together with other authors
such as Hanson and Younés [10], do not believe the
difference to be one of substance, but merely one of
application. Yes, the actual hands-on design will follow a
different path in either of the two practices, yet the two
processes rely on a basically similar mathematical
structure, hence on each other. Both design methods can lead
to optimal results that are adapted to human functions and
sensibilities.

For certain situations, applying either bottom-up design or
traditional top-down design is more efficient. Traditional
top-down design gives consistent, predictable results,
whereas bottom-up design gives unexpected, more novel
configurations. The price for novelty and greater freedom is
a larger number of steps, and consequently more time
invested in the project. The possibility of combining
bottom-up design with traditional top-down design has
already been proposed by Hanson and Younés [10] (in what
they call the "Third Way"). There is essentially one
adaptive design process, and different practitioners may
choose to carry out its steps either in a virtual
environment (i.e. inside their heads), or in the real world.
In the latter case, it is possible to involve more people in
the selection process, so that the design becomes
"participatory".

7. Collective intelligence.

This section draws on work by Francis Heylighen [12].
Heylighen defines intelligence as the ability to solve
problems. Sometimes, as occurs in colonies of social insects
such as termites and bees, intelligence is an emergent
property, since each individual alone does not have the
requisite neuronal capacity [7]. In the case of human
beings, each individual does have advanced intelligent
capacity, yet it is sometimes necessary to use a combination
of minds in order to solve a complex problem [12]. A city
works with complex mechanisms that together are too much for
any individual human comprehension. A city built over time
is the product of the collective intelligence of generations
of people acting together, either in a spatial grouping or
in a temporal perspective.

Despite the distinction between top-down and bottom-up
design implementations, both represent an application of
collective intelligence, but in very different ways. The
selection process that generates a design solution via
bottom-up methods is the result of actions and decisions by
a host of individual inputs. A collective design project
includes selection by the architect (or a group of
architects), end-users, and environmental forces. All those
forces are perceived and inputted into the selection process
by human agents acting as a collective intelligence. Such
forces may or may not be perceivable by the individual
designer in a bottom-up process, because of their number and
complexity.

Adaptive top-down implementation also uses collective
intelligence. The built environment is a common repository
of stored information. Developments having to do with forms
and structures that are adaptive to human physical, sensory,
and psychological needs are stored in pre-modernist built
structures. This information represents the work of an
enormous number of individuals, as well as collective
efforts throughout the ages. It has the advantage of being
accessible to everyone. Unlike information stored in books,
which until relatively recently was accessible only to an
educated class, information stored in built form is
immediately accessible, and acts as a working memory for
society.

The storage capacity of such a collective memory is far
larger than the memory capacity of any individual human
being [12]. Top-down design is helped by using encoded
information from traditional typologies -- these broaden the
intelligence of the individual designer or group of
collective designers. A top-down design implementation that
utilizes traditional typologies therefore extends human
intelligence into the built environment, by incorporating
the experience of other people from the past. On the other
hand, the deliberate destruction of the traditional built
environment, which was perpetrated by the modernists, erased
society's collective memory. This act reduced society's
collective intelligence, and severely limited its ability to
solve architectural and urban problems.

The built environment is the medium in which adaptive design
solutions have evolved (and are still evolving). Exploration
of innovative designs relies on selection and checking
against adaptive examples stored in the collective (built)
memory. Adaptive designs enhance human life; they are an
inseparable part of humanity's healthy functioning. Designs
that damage this life represent pathologies, which would
normally be rejected when recognized as such. A particular
group of people (incredibly, the professionals in those
disciplines) have been promoting a pathological type of
structure both on the architectural and urban scales. As
human intelligence no longer extends to the built
environment, it cannot protect us against architectural and
urban pathologies, which therefore proliferate.

Results linking the human mind with our surroundings are
slowly accumulating in the sciences. The fact that what we
build reflects how we think is becoming more and more
obvious; buildings and cities try to adapt to changing
circumstances just as an intelligent entity does to changes
in its environment. An adaptive design solves a problem --
and problem solving is what defines intelligence [12]. This
requires the free evolution of alternative solutions, and
unrestricted feedback and selection mechanisms to be in
place. Positive feedback in a system helps to generate the
pool of competing solutions, whereas negative feedback
identifies the non-adaptive ones.

Human concepts of organization and complexity are encoded
almost exclusively in our artifacts and built environment.
Our innate grasp of complexity, reinforced by observations
of natural complexity, makes possible all of our
technological achievements. This knowledge has not been
translated into a general theoretical formulation of
complexity -- a great deal of what we do understand works on
an intuitive level. Models describing organization and
complexity are very recent, and far more limited than
working examples of complex machines or software. Our
collective intelligence thus relies on information stored in
the environment to understand (and create) organized
complexity, but the architectural and urban components of
this external built memory are being erased at an alarmingly
rapid pace.

8. Emergence and self-organization.

Every city, piece of urban fabric, and building is a product
of emergence. This expresses the notion that a whole is more
than the sum of its individual parts; urban and
architectural components come together to create in the best
instances a unity that takes on a "life" of its own [7]. The
greatest buildings and urban complexes of mankind are just
made of bricks, wood, stones, tiles, etc. Yet they transcend
their materials so as to induce feelings of profound
emotional intensity in observers. This is a manifestation of
emergence. Something profound is created by the
coherent joining of mundane materials. In past centuries,
people understood this process in religious terms -- an
ecstatic experience was naturally associated with a great
building or urban space.

The opposite effect is also instructive. Many megalomaniac
architects and patrons have tried, unsuccessfully, to create
an impressive structure by using the most ostentatious and
expensive materials. The result is in many cases mediocre,
whereas a truly great building may be seen to be composed of
ordinary and even cheap (inexpensive, but not shoddy)
materials. What communicates to human beings is the
ensemble's overall coherence -- the emergent properties of
all the components coming together.

An emergent property in a system may be understood as the
organizational connective structure that evolves on top of
the components themselves [7]. This is analogous to the
meaning in a sentence compared to the individual letters
presented in no particular order. Emergence is identified
with information, meaning, learning, and connective
subsystems. Architectural and urban components on all scales
are the physical substrate on which information is encoded,
and the organization of this information produces meaning.
Both traditional architecture and "patterns" contain
connective rules that can generate meaning from ordering and
linking built components. A simplistic architectural
language prevents emergence.

Emergent systems are irreducible: they cannot be understood
in terms of their components alone, just as a sentence's
meaning cannot be communicated just by knowing all the
letters used. Emergence is invariably the product of
evolution, which brings us back to the issue of
understandability. Man-made systems that evolve in
complexity eventually reach a complexity threshold beyond
which it becomes difficult to understand how they work as a
whole. That should not prevent us from using them, however.
Whether we have a complex program, traditional mixed-use
urban fabric, or traditional architectural forms and
"patterns", such solutions represent an evolved exploration
of solution space.

An emergent solution on the architectural or urban scales
may be surprising, precisely because of its novelty, and
would be eliminated by imposing a simple understandable form
from above. That is how modernist and Fascist architectures
prevent emergence. Traditional architecture accepts novelty
and organizes it so that it is adaptive. At this time,
however, an arbitrary non-understandable form is often
imposed from above in an attempt to create novelty. This
fashion reflects a fundamental misunderstanding of
morphogenesis by the architectural and urban profession,
which has unfortunately fooled the general public. Such
non-adaptive novel forms are not evolved. Since they are not
solutions, they do not increase our collective intelligence.

Any dynamic complex system, if it is able to do so, will try
to organize its complexity so as to optimize energy flow.
This response or self-organization can be interpreted as a
kind of "learning", though it is not always in directions
that human beings either approve of or understand. The
sorting algorithm discussed previously is emergent, and
sometimes emergence creates unexpected properties, as was
noted. A system that is not selected for human use might
develop unexpected features and unwanted (not particularly
useful, or even harmful) properties. After all, viruses are
products of evolution.

Self-organization is a property of a system that uses
internal forces to influence its own structure or growth.
That is, it is generated by some algorithm which causes it
to develop internal coherence. We may not understand
entirely how self-organization works, but it is seen in many
natural systems. For example, snowflakes, spider webs,
cauliflowers, eddies and whorls in fluids, etc. exhibit
self-organization. Fractal form is an example of
self-organization. Any natural pattern that shows
organization on every level of magnification is the product
of some mechanism of self-organization.

There is a crucial difference between self-organization and
adaptivity, however. Whereas self-organization is driven
primarily by internal constraints, adaptivity is driven by
external constraints, so the system has to be open. A system
may self-organize but not be adaptive; it is independent of
its surroundings -- that is, closed [7]. A complex fractal
need not adapt to anything outside its own symmetry. In that
case, it develops the same intricate pattern regardless of
where it grows. An adaptive system, on the other hand,
whether it self-organizes or not, develops according to
input from its surroundings. A snowflake-shaped city plan
may be interesting because of the fractal interfaces it
offers, yet it does not adapt to human activities. The same
goes for a fractal pattern on a building -- it's really only
an abstract decoration.

9. Adaptivity and feedback.

The key to adaptivity is having a mechanism for feedback.
Without feedback, there is no way of incorporating ambient
information into the algorithm for growing a complex system.
Both the brain, and living structure, depend for their
function on an enormous amount of feedback. Dead matter has
no feedback. Contemporary architecture, following the early
modernists, has dispensed with feedback. Architects wish to
impose their dead abstract forms on people, who are not
supposed to question them. Indeed, any feedback about
building and city form and functions is considered a
nuisance, since it implies that the original "ideal" forms
were not perfect.

Feedback is a two-way influence occurring in two distinct
contexts: (1) among system components of the same size; and
(2) among different levels of the system. Units or
mechanisms act in parallel on any level, and their output is
available to each other, and to the higher levels. An
adaptive system will use feedback to influence both the
smaller and larger scales. Without feedback, there is either
no connectivity, or the connectivity is disorganized -- the
opposite of what one requires in a coherent complex system.

The chief flaw in a top-down implementation is that it might
ignore forces that would make it truly adaptive. The only
way to guarantee that this does not happen is to make sure
that each design step is adaptive to the situation at hand.
By focussing on each step in the process, one defocuses from
the final result, so that one allows for divergence from an
initial rigid goal. It is often the case that the best
result departs from an initial specification [13]. Going
directly to a fixed end product, by contrast, does not
necessarily follow a sequence of steps in which every single
step is adaptive, and thus the final result is weaker.

Modernist architects confused people by substituting
precision and elegance for human connections. Precision
represents a matching to a mechanical ideal that has nothing
to do with human uses or sensibilities. It is a strictly
abstract idea that relates to pure geometry. Adaptation to
human comfort, on the other hand, abandons mechanical
precision, because structures that satisfy human needs are
most often loose and accommodating. It is well-known that
mankind's most memorable and inspiring architectural
achievements are neither extremely precise, nor perfectly
aligned, nor do they obey an absolute geometry. Furthermore,
vernacular architecture, which is more psychologically
comfortable than any of today's sterile mass-produced
buildings, evolved by paying unrelenting attention to
emotional and sensory feedback and not to mechanical
precision.

An adaptive design evolves according to how it satisfies
requirements for its use. It adapts to a set of conditions;
usually having to do with its relation to internal and
external forces. A building, for example, will be initially
adaptive if its design has evolved so as to satisfy the
needs of future occupants. A building may also evolve after
it is built, by means of structural adaptive changes to its
fabric driven by the need to satisfy the current needs of
new occupants. This second adaptation is much more prevalent
in practice and is a characteristic of successful
architecture throughout the ages, even though it is
insufficiently recognized by architectural academics [14].

It is difficult even to talk about architectural adaptivity,
since architecture has cut itself off from feedback
mechanisms. By contrast, adaptivity is the most obvious
feature of other disciplines. For example, in Computer
Science, the test is straightforward and uncompromising:
does a program run; and does it compute what it is supposed
to? The feedback is immediate; if either a program crashes,
or if it runs but gives a result that is independently
checked to be wrong, the program is dysfunctional. We really
don't have an analogous solid test of adaptivity in
architecture, and this lacuna in the very foundations of the
discipline has created enormous problems.

I will use the sorting algorithm discussed previously in an
analogy of what contemporary architects do. As a
hypothetical illustration, architectural theorists might
take an arbitrary set of switching and comparing
instructions, and declare them to be a program. They would
carefully avoid running it, since that would immediately
invalidate their claim that this nonsense jumble of lines of
code actually does anything. Their justification would rest
strictly on superficial appearance: since lines of code
look like a program, that's all there is to programming.
They might go further, moreover, and declare this
non-program's incomprehensibility to be a philosophical
virtue, following the French deconstructivist philosophers
[9]. I would not be surprised if then, someone picks 55
switching instructions at random and declares a new champion
for the n = 16 sorting network, again without ever
running anything on a computer.

10. Conclusion.

Architecture needs to be based on a scientific understanding
of adaptive design principles. I described Darwinian
processes and their role in design, using the evolution of a
computer program (a number-sorting algorithm) to make a
point. Evolved solutions acquire a complexity that often
exceeds the intelligence of an individual human being. For
this reason, the traditional built environment is a product
of a collective intelligence (such as shown by social
insects) applied to deepen the human understanding of form.
Adaptive top-down and bottom-up design methods were
explained with reference to results from complexity theory.
An old misunderstanding, which considered top-down and
bottom-up methods to be mutually contradictory, was cleared
up -- in fact, as long as they are truly adaptive, the two
methods are mathematically equivalent.

I also criticized the arbitrariness of non-adaptive design
methods in widespread use for the past several decades.
Architects who replaced historic solutions adapted to human
needs with simplistic image-driven typologies revealed a
total lack of understanding for the role of design. They
also introduced an arrogance into the profession, which,
combined with those non-adaptive design methods, has made
the built environment more and more dysfunctional and even
inhuman. It appears that despite repeated and
well-publicized calls for design according to adaptive
principles, these tendencies of contemporary architecture
and urbanism show no signs of abating. I believe that it is
time to rebuild a functional environment that better
supports human life. This paper suggested a basis for doing
so.